User health management for mobile devices

Abstract

Embodiments are directed towards embodiments for monitoring or predicting user health with respect their use of connected computers, such as, mobile phones, tablets, or the like. Activities associated with a user and a computing device may be monitored to determine activity events. One or more sub-scores may be provided in real time based on metrics provided as input to sub-score models such that the metrics are associated with the activity events. A health score associated with a probability of an occurrence of adverse user outcomes may be provided based on a health model that uses the sub-scores. An analysis engine may compare the health score to other health scores to predict in real time the adverse outcomes. The analysis engine may recommend one or more actions to decrease the probability of the occurrence of the adverse outcomes based on the result.

What is claimed as new and desired to be protected by Letters Patent of the United States is: 
     
       1. A method for managing operations over a network using one or more network computers that include one or more processors that perform actions, comprising:
 instantiating one or more user management engines to perform actions, including:
 monitoring one or more activities associated with a user and a computing device to determine one or more activity events, wherein the one or more activity events include one or more interrupt events; 
 determining one or more sub-scores in real time based on one or more metrics being provided as input to one or more provided sub-score models, wherein the one or more metrics are associated with the one or more activity events; and 
 providing a health score that is associated with a probability of an occurrence of one or more adverse user outcomes based on a health model that uses the one or more sub-scores; and 
 
 instantiating an analysis engine to perform actions, including:
 comparing the health score to one or more other health scores, wherein the comparison is employed to reduce an amount of computing resources used to predict in real time the one or more adverse outcomes; and 
 updating one or more coefficients of the one or more sub-score models when a result of the comparison exceeds a threshold; and 
 recommending one or more actions to decrease the probability of the occurrence of the one or more adverse outcomes based on the result, wherein the one or more recommended actions are provided in a report. 
 
 
     
     
       2. The method of  claim 1 , wherein the one or more user management engines perform further actions, including:
 providing telemetry information that is associated with the user based on one or more sensors, wherein the telemetry information includes one or more of pulse rate information, physical activity levels, gyroscopic data, or accelerometer data; and 
 providing one or more additional metrics based on the telemetry information; and 
 modifying the one or more sub scores based on the one or more additional metrics. 
 
     
     
       3. The method of  claim 1 , wherein the one or more user management engines perform further actions, including:
 determining one or more activities that are associated with the one or more adverse outcomes; 
 determining an amount of harm contributed by the one or more activities; and 
 communicating the amount of harm contributed by the one or more activities to one or more services or organizations that manage or manufacture the computing device. 
 
     
     
       4. The method of  claim 1 , further comprising, instantiating a modeling engine, that performs actions, including:
 providing the one or more sub-score models based on the metrics; and 
 providing the health model based on the one or more sub-score models. 
 
     
     
       5. The method of  claim 1 , wherein the one or more metrics, further comprise one or more values that represent one or more of a measure of mean hour of day notifications received, a proportion of interrupting events during user sleep hours, a proportion of interrupt events during user meal hours, a measure of notification variation throughout a time period, a proportion of email notifications, an amount of time the user spends on non-utility applications, an amount of user interaction with the computing device that occurs before user sleep hours, or a proportion of interrupt events that occur during weekends, wherein the one or more values may be provided from continuous data or discrete data. 
     
     
       6. The method of  claim 1 , wherein the one or more adverse outcomes include one or more of cognitive degradation, sleeplessness, internet addiction, or reduced productivity by the user. 
     
     
       7. The method of  claim 1 , wherein the one or more user management engines perform further actions, including, predicting a health score based on the one or more metrics and the one or more sub-score models and the health model. 
     
     
       8. The method of  claim 1 , wherein the one or more user management engines perform further actions, including, providing health scores that are associated with one or more of applications, services, or one or more types of the computing device. 
     
     
       9. A system for managing operations over a network, comprising:
 a network computer, comprising:
 a transceiver that communicates over the network; 
 a memory that stores at least instructions; and 
 one or more processors that execute instructions that perform actions, including:
 instantiating one or more user management engines to perform actions, including:
 monitoring one or more activities associated with a user and a computing device to determine one or more activity events, wherein the one or more activity events include one or more interrupt events; 
 determining one or more sub-scores in real time based on one or more metrics being provided as input to one or more provided sub-score models, wherein the one or more metrics are associated with the one or more activity events; and 
 providing a health score that is associated with a probability of an occurrence of one or more adverse user outcomes based on a health model that uses the one or more sub-scores; and 
 instantiating an analysis engine to perform actions, including: 
 comparing the health score to one or more other health scores, wherein the comparison is employed to reduce an amount of computing resources used to predict in real time the one or more adverse outcomes; and 
 updating one or more coefficients of the one or more sub-score models when a result of the comparison exceeds a threshold; and 
 recommending one or more actions to decrease the probability of the occurrence of the one or more adverse outcomes based on the result, wherein the one or more recommended actions are provided in a report; and 
 
 
 
 one or more other network computers, comprising:
 another transceiver that communicates over the network; 
 another memory that stores at least instructions; and 
 one or more processors that execute instructions that perform actions, including:
 providing information associated with one or more portions of the one or more activities. 
 
 
 
     
     
       10. The system of  claim 9 , wherein the one or more user management engines perform further actions, including:
 providing telemetry information that is associated with the user based on one or more sensors, wherein the telemetry information includes one or more of pulse rate information, physical activity levels, gyroscopic data, or accelerometer data; and 
 providing one or more additional metrics based on the telemetry information; and 
 modifying the one or more sub scores based on the one or more additional metrics. 
 
     
     
       11. The system of  claim 9 , wherein the one or more user management engines perform further actions, including:
 determining one or more activities that are associated with the one or more adverse outcomes; 
 determining an amount of harm contributed by the one or more activities; and 
 communicating the amount of harm contributed by the one or more activities to one or more services or organizations that manage or manufacture the computing device. 
 
     
     
       12. The system of  claim 9 , further comprising, instantiating a modeling engine, that performs actions, including:
 providing the one or more sub-score models based on the metrics; and 
 providing the health model based on the one or more sub-score models. 
 
     
     
       13. The system of  claim 9 , wherein the one or more metrics, further comprise one or more values that represent one or more of a measure of mean hour of day notifications received, a proportion of interrupting events during user sleep hours, a proportion of interrupt events during user meal hours, a measure of notification variation throughout a time period, a proportion of email notifications, an amount of time the user spends on non-utility applications, an amount of user interaction with the computing device that occurs before user sleep hours, or a proportion of interrupt events that occur during weekends, wherein the one or more values may be provided from continuous data or discrete data. 
     
     
       14. The system of  claim 9 , wherein the one or more adverse outcomes include one or more of cognitive degradation, sleeplessness, internet addiction, or reduced productivity by the user. 
     
     
       15. The system of  claim 9 , wherein the one or more user management engines perform further actions, including, predicting a health score based on the one or more metrics and the one or more sub-score models and the health model. 
     
     
       16. The system of  claim 9 , wherein the one or more user management engines perform further actions, including, providing health scores that are associated with one or more of applications, services, or one or more types of the computing device. 
     
     
       17. A processor readable non-transitory storage media that includes instructions for managing operations over a network, wherein execution of the instructions by one or more hardware processors performs actions, comprising:
 instantiating one or more user management engines to perform actions, including:
 monitoring one or more activities associated with a user and a computing device to determine one or more activity events, wherein the one or more activity events include one or more interrupt events; 
 determining one or more sub-scores in real time based on one or more metrics being provided as input to one or more provided sub-score models, wherein the one or more metrics are associated with the one or more activity events; and 
 providing a health score that is associated with a probability of an occurrence of one or more adverse user outcomes based on a health model that uses the one or more sub-scores; and 
 
 instantiating an analysis engine to perform actions, including:
 comparing the health score to one or more other health scores, wherein the comparison is employed to reduce an amount of computing resources used to predict in real time the one or more adverse outcomes; and 
 updating one or more coefficients of the one or more sub-score models when a result of the comparison exceeds a threshold; and 
 recommending one or more actions to decrease the probability of the occurrence of the one or more adverse outcomes based on the result, wherein the one or more recommended actions are provided in a report. 
 
 
     
     
       18. The media of  claim 17 , wherein the one or more user management engines perform further actions, including:
 providing telemetry information that is associated with the user based on one or more sensors, wherein the telemetry information includes one or more of pulse rate information, physical activity levels, gyroscopic data, or accelerometer data; and 
 providing one or more additional metrics based on the telemetry information; and 
 modifying the one or more sub scores based on the one or more additional metrics. 
 
     
     
       19. The media of  claim 17 , wherein the one or more user management engines perform further actions, including:
 determining one or more activities that are associated with the one or more adverse outcomes; 
 determining an amount of harm contributed by the one or more activities; and 
 communicating the amount of harm contributed by the one or more activities to one or more services or organizations that manage or manufacture the computing device. 
 
     
     
       20. The media of  claim 17 , further comprising, instantiating a modeling engine, that performs actions, including:
 providing the one or more sub-score models based on the metrics; and 
 providing the health model based on the one or more sub-score models. 
 
     
     
       21. The media of  claim 17 , wherein the one or more metrics, further comprise one or more values that represent one or more of a measure of mean hour of day notifications received, a proportion of interrupting events during user sleep hours, a proportion of interrupt events during user meal hours, a measure of notification variation throughout a time period, a proportion of email notifications, an amount of time the user spends on non-utility applications, an amount of user interaction with the computing device that occurs before user sleep hours, or a proportion of interrupt events that occur during weekends, wherein the one or more values may be provided from continuous data or discrete data. 
     
     
       22. The media of  claim 17 , wherein the one or more adverse outcomes include one or more of cognitive degradation, sleeplessness, internet addiction, or reduced productivity by the user. 
     
     
       23. The media of  claim 17 , wherein the one or more user management engines perform further actions, including, predicting a health score based on the one or more metrics and the one or more sub-score models and the health model. 
     
     
       24. A network computer for managing operations over a network, comprising:
 a transceiver that communicates over the network; 
 a memory that stores at least instructions; and 
 one or more processors that execute instructions that perform actions, including:
 instantiating one or more user management engines to perform actions, including:
 monitoring one or more activities associated with a user and a computing device to determine one or more activity events, wherein the one or more activity events include one or more interrupt events; 
 determining one or more sub-scores in real time based on one or more metrics being provided as input to one or more provided sub-score models, wherein the one or more metrics are associated with the one or more activity events; and 
 providing a health score that is associated with a probability of an occurrence of one or more adverse user outcomes based on a health model that uses the one or more sub-scores; and 
 
 instantiating an analysis engine to perform actions, including:
 comparing the health score to one or more other health scores, wherein the comparison is employed to reduce an amount of computing resources used to predict in real time the one or more adverse outcomes; and 
 updating one or more coefficients of the one or more sub-score models when a result of the comparison exceeds a threshold; and 
 recommending one or more actions to decrease the probability of the occurrence of the one or more adverse outcomes based on the result, wherein the one or more recommended actions are provided in a report. 
 
 
 
     
     
       25. The network computer of  claim 24 , wherein the one or more user management engines perform further actions, including:
 providing telemetry information that is associated with the user based on one or more sensors, wherein the telemetry information includes one or more of pulse rate information, physical activity levels, gyroscopic data, or accelerometer data; and 
 providing one or more additional metrics based on the telemetry information; and 
 modifying the one or more sub scores based on the one or more additional metrics. 
 
     
     
       26. The network computer of  claim 24 , wherein the one or more user management engines perform further actions, including:
 determining one or more activities that are associated with the one or more adverse outcomes; 
 determining an amount of harm contributed by the one or more activities; and 
 communicating the amount of harm contributed by the one or more activities to one or more services or organizations that manage or manufacture the computing device. 
 
     
     
       27. The network computer of  claim 24 , further comprising, instantiating a modeling engine, that performs actions, including:
 providing the one or more sub-score models based on the metrics; and 
 providing the health model based on the one or more sub-score models. 
 
     
     
       28. The network computer of  claim 24 , wherein the one or more metrics, further comprise one or more values that represent one or more of a measure of mean hour of day notifications received, a proportion of interrupting events during user sleep hours, a proportion of interrupt events during user meal hours, a measure of notification variation throughout a time period, a proportion of email notifications, an amount of time the user spends on non-utility applications, an amount of user interaction with the computing device that occurs before user sleep hours, or a proportion of interrupt events that occur during weekends, wherein the one or more values may be provided from continuous data or discrete data. 
     
     
       29. The network computer of  claim 24 , wherein the one or more adverse outcomes include one or more of cognitive degradation, sleeplessness, internet addiction, or reduced productivity by the user. 
     
     
       30. The network computer of  claim 24 , wherein the one or more user management engines perform further actions, including, predicting a health score based on the one or more metrics and the one or more sub-score models and the health model.